ICON The new global nonhydrostatic model of DWD and MPI-M Daniel Reinert1, Günther Zängl1, and the ICON-team1,2 1Deutscher Wetterdienst / 2Max-Planck-Institute for Meteorology 13th EMS Annual Meeting 09 – 13 September 2013, Reading, United Kingdom

ICON – ICOsahedral Nonhydrostatic Model DWD MPI Joint development project of DWD and Max-Planck-Institute for Meteorology for building a next-generation global NWP and climate modelling system Atmosphere and ocean model Outline Project goals Horizontal grid structure and accompanying problems ICON NWP physics suite Selected results Roadmap and Summary Daniel Reinert – 12.09.2013

Primary development goals Improved conservation properties (at least mass) and consistent tracer transport (tracer air-mass consistency) Applicability on a wide range of scales from 100 km to  1 km Scalability and efficiency on massively parallel computer architectures with O(104 +) cores Local refinement/nesting capability Horizontal grid with nest over Europe At DWD: Replace current global model GME Replace regional model COSMO-EU by a high-resolution window over Europe. At MPI-M: Use ICON as dynamical core of an Earth System Model (MPI-ESM2) Daniel Reinert – 12.09.2013

ICON’s unstructured grid Primal cells: triangles uses icosahedron for macro triangulation C-type staggering: local subdomains (“nests”) velocity at edge midpoints mass at cell circumcenter Triangular C-Grid local domain(s) global domain Daniel Reinert – 12.09.2013

Equations (dry adiabatic) and solver Fully compressible nonhydrostatic vector invariant form, shallow atm. Solver: Finite volume/finite difference discretization (mostly 2nd order) Two-time level predictor-corrector time integration Vertically implicit (vertical sound-wave propagation) Fully explicit time integration in the horizontal (at sound wave time step; not split explicit!) Mass conserving Daniel Reinert – 12.09.2013

Checkerboard noise on triangular C-Grid Main problem with triangular C-grid: suffers from spurious computational mode (e.g. Danilov (2010)), triggered by the discretized divergence operator (Wan (2013)) Divergence operator: applies the Gauss theorem Truncation error (Wan (2013)): Only 1st order accurate on triangular C-grid Error changes sign from upward- to downward pointing triangle  checkerboard Example for synthetic velocity field (Wan, 2013) Daniel Reinert – 12.09.2013

Controlling the checkerboard noise Goal: Eliminate 1st order error Basic idea: Divergence averaging I: Compute standard 1st order div II: Compute divergence estimate based on immediate neighbors (2nd order bilinear interpolation) III Averaging: 2nd order accurate for isosceles triangles Daniel Reinert – 12.09.2013

Example: Baroclinic wave Jablonowski-Williamson (2006) baroclinic wave test case PS T Daniel Reinert – 12.09.2013

Example: Baroclinic wave Jablonowski-Williamson (2006) baroclinic wave test case PS T Standard divergence operator Divergence averaging div div “checkerboard” noise Daniel Reinert – 12.09.2013

ICON NWP-physics Process Author Scheme Origin Radiation Mlawer et al. (1997) Barker et al. (2002) RRTM ECHAM6 Non-orographic gravity wave drag Scinocca (2003) Orr, Bechthold et al. (2010) wave dissipation at critical level IFS Cloud cover Köhler et al. (new development) diagnostic (later prognostic) PDF ICON Microphysics Doms and Schättler (2004) Seifert (2010) prognostic: water vapour, cloud water, cloud ice, rain, snow COSMO Saturation adjustment Blahak (2010) isochoric adjustment Convection Tiedtke (1989) Bechthold et al. (2008) mass-flux shallow and deep Sub-grid scale orographic drag Lott and Miller (1997) blocking, GWD Turbulent transfer / diffusion Raschendorfer (2001) prognostic TKE Soil/surface Heise and Schrodin (2002) Mironov and Ritter (2004) Mironov (2008) TERRA (tiled + multi-layer snow) SEAICE FLAKE(fresh water lake scheme) GME/COSMO Daniel Reinert – 12.09.2013

Reduced grid for radiation Hierarchical structure of the triangular mesh is very attractive for calculating physical processes (e.g. radiative transfer) with different spatial resolution compared to dynamics. upscaling Radiation step Empirical corrections Radiative transfer computations every 30min downscaling Daniel Reinert – 12.09.2013

Proof of concept net surface shortwave flux (reduced – full grid) average over 30 x 48h forecast runs in June 2012 Avg: 1.57 Reduced radiation grid currently generates positive bias in Daniel Reinert – 12.09.2013

Flat-MPI performance Recall goal: scalability up to O(104+) cores time (s) 1024 4096 1024 4096 MPI tasks Test setup: ICON RAPS 2.0, IBM Power 7 20/10/5 km, 8h forecast, reduced radiation grid (S. Körner, DWD, 03/2013) Daniel Reinert – 12.09.2013

Selected results of NWP test suite Real-case 7-day forecasts with interpolated IFS analysis data WMO standard verification against IFS analysis on 1.5° lat/lon grid. Comparison against GME reference experiment with interpolated IFS analysis data. ICON40L90 GME40L60 hor. resolution 40 km vertical levels 90 60 top height 75 km 36 km analysis data IFS Basic requirement for operational use of ICON ICON must outperform GME in terms of forecast quality/scores Daniel Reinert – 12.09.2013

Verification: Surface Pressure, January 2012 Region: Northern hemisphere (NH) ICON GME against IFS SH: 21% Verification: G. Zängl, U. Damrath, 08/2013 (DWD) Daniel Reinert – 12.09.2013

Verification: Geopot 500 hPa, January 2012 Region: Northern hemisphere (NH) ICON GME against IFS SH: 9.4% Verification: G. Zängl, U. Damrath, 08/2013 (DWD) Daniel Reinert – 12.09.2013

Verification: Rh 700 hPa, January 2012 Region: Tropics (Tr) ICON GME against IFS ICON shows strong positive moisture bias in the tropics Verification: G. Zängl, U. Damrath, 08/2013 (DWD) Daniel Reinert – 12.09.2013

Roadmap towards operational application Daniel Reinert – 12.09.2013

Summary ICON is entering the home stretch for becoming operational Verification results are mostly exceeding those of GME, but there are still some weaknesses/biases e.g. moisture field Technical parts scale on massively parallel systems (I/O still needs performance improvements) Optimization of forecast quality still ongoing Tests with own 3D-Var data assimilation have started recently. Daniel Reinert – 12.09.2013

Thank you for your attention !!